Method and system for performing image mark recognition

ABSTRACT

A method and system for performing image mark recognition for a document is disclosed. A document is scanned into a digital image. Reference image marks are sensed from the digital image. The reference image marks may include trigger row marks and/or corner/crop marks. Coordinates denoting the location of cells within the digital image are determined base on the locations of the reference image marks. Response marks are evaluated for darkness, opacity, and/or grayness on a pixel-by-pixel basis. The response marks are each assigned a percentage value based on the ratio between a total color value for a cell and a maximum color value for a cell.

FIELD OF THE INVENTION

The present invention generally relates to the field of markrecognition. The present invention particularly relates to scanning animage of a document and performing mark recognition on the scannedimage. In an embodiment, a response mark may be indicative of anintended response to a question and/or may be representative of codedinformation. In a preferred embodiment, the present invention provides ahardware independent methodology for evaluating the presence or absenceof one or more marks on a document, which may be configured to higher orlower resolutions as needed.

BACKGROUND OF THE INVENTION

Conventional mark reading systems have been employed to extractinformation, such as pencil marks, from a document. These systemstypically include a scanner configured to read marks from the document.The scanner creates a digitized representation of the document. Thedigitized document is then processed by a separate application toevaluate the document. In an assessment environment, this system can beused to score examination responses. For example, many students andother examinees are familiar with the typical response format foranswering multiple choice questions which requires the student tofill-in a space (e.g. a circle, square, etc.) associated with thequestion. Mark reading systems can grade such answer sheetssignificantly faster and more accurately than a human grader. However,conventional mark reading systems are limited by the accuracy with whichthe document is digitized. Increased accuracy is available with moresophisticated and more expensive systems. When a high degree of accuracyis required, expensive scanning equipment can be purchased which willprovide a digitized representation of the document within most acceptederror rates. However, in addition to the expense associated with suchsystems, they may not be easily configured to alternate environmentswhere differing accuracy levels are required. When accuracy in thedigitizing process is sacrificed, such systems often improperly gradetest answers. For example, the systems may not recognize properly markedtarget areas that are incompletely filled or in which the pencil markingis lighter than a threshold value. Moreover, the systems may recognizestray marks and erasures as incorrect answers when a test taker did notintend such an answer.

A particularly egregious error may result when a test taker properlymarks a correct answer for a question, but a mark reading systemrecognizes a stray mark or erasure as an incorrect answer for the samequestion. In this case, although the test taker correctly answered thequestion, the test taker would not receive credit because the systemwould report that the test taker provided two answers. As such, the testtaker may be penalized because of the medium in which the test ispresented rather than the substantive material on which the test isbased.

What is needed is an improved image mark recognition system that canaccurately evaluate the marks on a document to be digitized which isboth cost effective and independent of the hardware being used to scanthe document.

SUMMARY OF PREFERRED EMBODIMENTS

Before the present methods, systems, and materials are described, it isto be understood that this invention is not limited to the particularmethodologies, systems and materials described, as these may vary. It isalso to be understood that the terminology used in the description isfor the purpose of describing the particular versions or embodimentsonly, and is not intended to limit the scope of the present inventionwhich will be limited only by the appended claims.

It must also be noted that as used herein and in the appended claims,the singular forms “a,” “an,” and “the” include plural references unlessthe context clearly dictates otherwise. Thus, for example, reference toa “mark” is a reference to one or more marks and equivalents thereofknown to those skilled in the art, and so forth. Unless definedotherwise, all technical and scientific terms used herein have the samemeanings as commonly understood by one of ordinary skill in the art.Although any methods, materials, and devices similar or equivalent tothose described herein can be used in the practice or testing ofembodiments of the present invention, the preferred methods, materials,and devices are now described. All publications mentioned herein areincorporated by reference. Nothing herein is to be construed as anadmission that the invention is not entitled to antedate such disclosureby virtue of prior invention.

The present invention relates to enhancing a scanned image of a documentor more accurately performing mark recognition of the scanned image todetermine the presence or absence of a mark. The methodology of thepresent invention begins after a document has been digitized. Thedigitized image is then mapped to a coordinate system. The mapping isperformed on the digitized image by using trigger rows, which aredetermined using existing marks on one margin of the document. Thetrigger rows are then logically extended across the document. Next, thepresent invention completes the mapping process by logically creatingcolumns orthogonal to the extended trigger rows. The number of columnscreated can vary and may be configured to the degree of accuracyrequired. Alternately, the mapping process may be performed by usingcorner marks (also known as anchor marks or crop marks), which are marksprinted at each corner of the document. A coordinate system is thencreated by determining the number of rows desired, which may vary, andequally dividing the space into horizontal rows, and by determining thenumber of columns desired, which may vary, and equally dividing thespace into vertical columns. Document deskew may also be performed.Those skilled in the art will understand that other methods for mappingthe digitized image to a coordinate system may also be used.

Next, a resolver engine evaluates each cell on a pixel-by-pixel basis.The pixel-by-pixel analysis results in a value for each cell. The valuemay represent the opacity of a response mark present in the cell. Theresult is that the digitized image has been converted into a series ofnumeric values each representing a potential response mark on theoriginal document.

In a preferred embodiment, a method of performing image mark recognitionincludes accessing a scanned image of a document containing a pluralityof image marks, performing reference image mark recognition on thescanned image, performing coordinate mapping on the scanned image todetermine coordinates for a plurality of cells within the scanned image,analyzing one or more pixels in each cell, and determining a cell colorvalue for each cell based on values assigned to the one or more pixels.In an embodiment, performing reference image mark recognition includesdetermining a location for each of one or more alignment marks and mayfurther include verifying image mark alignment and spacing based on aresolution of the scanned image and the locations of the one or morealignment marks. In an embodiment, determining the location of one ormore alignment marks includes examining each corner of the scannedimage. In an embodiment, determining the location of one or morealignment marks includes searching for trigger rows on at least onemargin of the scanned image.

In an embodiment, performing coordinate mapping includes computinglogical row coordinates for a number of rows in the scanned image,computing logical column coordinates for a number of columns in thescanned image, creating a mapping within the scanned image, andresolving the mapping into coordinate values for each of a plurality ofcells. In an embodiment, computing logical row coordinates and logicalcolumn coordinates includes using one or more trigger marks as referencepoints. In an embodiment, computing logical row coordinates and logicalcolumn coordinates includes using one or more corner marks as referencepoints. The number of rows and the number of columns may beautomatically determined based on the step of performing reference imagemark recognition. Alternately, the number of rows and the number ofcolumns may be pre-determined. In an embodiment, creating a mappingincludes determining absolute pixel positions for each cell within thescanned document as defined by an intersection of a row and a column.

In an embodiment, analyzing one or more pixels includes incrementing atotal color value by a color value for each pixel in a cell. Determininga cell color value may include setting the cell color value to the ratioof the total color value to a maximum color value.

In a preferred embodiment, a system for performing image markrecognition includes a processor and one or more computer readablemediums operatively coupled to the processor. At least one of the one ormore computer readable mediums contains a scanned image of a document.At least one of the one or more computer readable mediums containscomputer program instructions for performing a method of performingimage mark recognition.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and form a part ofthe specification, illustrate preferred embodiments of the presentinvention and, together with the description serve to explain theprinciples of the invention. The embodiments illustrated in the drawingsshould not be read to constitute limiting requirements, but instead areintended to assist the reader in understanding the invention.

FIG. 1 depicts an exemplary process flow for the image mark recognitionprocess according to an embodiment of the present invention.

FIG. 2 depicts an exemplary cell evaluation ordering according to anembodiment of the present invention.

FIGS. 3A and 3B depict exemplary computations of cell color valuesaccording to an embodiment of the present invention.

FIG. 4 is a block diagram of exemplary internal hardware that may beused to contain or implement the program instructions of a systemembodiment of the present invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The present invention relates to resolving a scanner image of a documentto perform mark recognition on the scanned image. The present inventionprovides a system and method for resolving a digitized image of adocument, independent of the hardware used to create the digitizedimage. The digitized image is enlisted by the present invention and asequence of values representing the presence or absence of responsemarks on the document is created. This sequence of values is thenavailable for use by any application which may be created to enhance thedocument, such as a scoring application which may be used to return ascore for an examination.

An aspect of the present invention involves mapping the digitized imageof a document to a coordinate system. This coordinate mapping may beperformed by detecting trigger row marks and/or corner/crop marks tocreate a logical document mapping. A trigger row mark is a mark on anedge of a document that denotes boundaries of a row logically extendingacross the document. In an assessment environment, responses may beentered within the logical rows. Each row for which a test taker canpotentially enter one or more responses may have a separate trigger rowmark. Alternatively, a trigger row mark may be used to denote everysecond row, third row, or any other pattern that may be used tologically subdivide a document. An alternate method of coordinatemapping includes use of corner/crop marks placed in each corner of thedocument. The crop marks are located and used to define the coordinatesystem by sub-dividing the space between the crop marks into a logicalcoordinate system. For example, adjacent crop marks along the verticalmargin of the document may be subdivided into a predetermined number ofequally sized rows. Similarly, adjacent crop marks along the horizontalmargin of the document may be subdivided into a predetermined number ofequally sized columns intersecting with the rows. The pre-determinednumber of rows and columns may be verified by analyzing the location ofthe response marks. Alternatively, a user may enter informationregarding the document, such as a document number, from which the rowand column placement is determined.

As shown in FIG. 1, the process begins by accessing the digital image ofa previously scanned document 105. The digital image may have beencreated by any means available and is not dependent on any particularhardware, format or resolution. A logical coordinate system is thenmapped over the digital image 110 using the trigger row technique, thecorner/crop mark techniques, or any other technique. The result of thecoordinate mapping process 110 is that the digital image of the documenthas been logically subdivided into a plurality of cells that, incombination, comprise the entire digital image. The number of cells isconfigurable during the mapping process, and more or fewer cells maypreferably be generated depending on the type of document being scannedand the processing required. The process then begins to iterativelyanalyze the image on a cell-by-cell basis to generate machine-readabledata representative of the response marks on the document. Thisiterative process begins by obtaining the image 115 in the first cell.For example, as shown in FIG. 2, the mapping process may create an (N×M)coordinate system requiring evaluation of N*M cells. This process may,for example, begin by evaluating cell (1,1) 205, proceed to cell (1,2)210 and continue in the same manner to cell (1,M) 215. Next, cell (2,1)220 through (2,M) 225 and so on to cell (N,M) 230 may be evaluated.Alternate cell evaluation orderings and numberings are considered to bewithin the scope of this invention.

Returning to FIG. 1, the process may resolve the response marks in eachcell into computer readable values. For each cell, a cell color valuefrom, for example, 0 to 100, inclusive, representing the amount ofdarkness/lightness of a cell's coloration may be assigned 120. The cellcolor value may be assigned 120 based on a ratio of the sum of colorvalues for each pixel in a cell having a non-white color (collectively,a total color value) to a maximum color value for the cell. The maximumcolor value may be equal to the number of pixels in a cell multiplied bya maximum pixel color value.

Two exemplary computations of a cell color value are shown in FIGS. 3Aand 3B. In the exemplary computations, each pixel within a cell may beassigned a pixel color value ranging from 0 to 15, inclusive. In FIG.3A, the cell has 4 pixels having a pixel color value equal to 0, 8pixels having a pixel color value equal to 4, 12 pixels having a pixelcolor value equal to 9, and 12 pixels having a pixel color value equalto 15. The total color value for the cell in FIG. 3A istc=(4*0)+(8*4)+(12*9)+(12*15)=32+108+180=320. The maximum color valuefor the cell in FIG. 3A is pc=(6 rows*6 columns*15)=540. The cell colorvalue for the cell in FIG. 3A is v=tc/pc≈59%. Thus, the cell color valuefor the cell in FIG. 3A is 59.

Similar computations are used to compute the total color value, maximumcolor value and cell color value in FIG. 3B. Here, tc=172, pc=540, andv≈32%. Hence, the cell color value for the cell in FIG. 3B is 32.

Preferably, a value of 0 may represent the lightest possible mark (e.g.,white), and a value of 100 may represent the darkest possible mark(e.g., black). The machine-readable data values for each cell mayoptionally be stored 125 to an output file.

FIG. 4 is a block diagram of exemplary internal hardware that may beused to contain or implement the program instructions of a systemembodiment of the present invention. Referring to FIG. 4, a bus 428serves as the main information highway interconnecting the otherillustrated components of the hardware. CPU 402 is the centralprocessing unit of the system, performing calculations and logicoperations required to execute a program. Read only memory (ROM) 418 andrandom access memory (RAM) 420 constitute exemplary memory devices.

A disk controller 404 interfaces with one or more optional disk drivesto the system bus 428. These disk drives may be external or internalfloppy disk drives such as 410, CD ROM drives 406, or external orinternal hard drives 408. As indicated previously, these various diskdrives and disk controllers are optional devices.

Program instructions may be stored in the ROM 418 and/or the RAM 420.Optionally, program instructions may be stored on a computer readablemedium such as a floppy disk or a digital disk or other recordingmedium, a communications signal or a carrier wave.

An optional display interface 422 may permit information from the bus428 to be displayed on the display 424 in audio, graphic or alphanumericformat. Communication with external devices may optionally occur usingvarious communication ports 426. An exemplary communication port 426 maybe attached to a scanner 430 used to scan an image of a document intoone or of the memory devices or disk drives.

In addition to the standard computer-type components, the hardware mayalso include an interface 412 which allows for receipt of data frominput devices such as a keyboard 414 or other input device 416 such as aremote control, pointer and/or joystick.

An embedded system may optionally be used to perform one, some or all ofthe operations of the present invention. Likewise, a multiprocessorsystem may optionally be used to perform one, some or all of theoperations of the present invention.

Although the invention has been described with reference to thepreferred embodiments, it will be apparent to one skilled in the artthat variations and modifications are contemplated within the spirit andscope of the invention. The drawings and description of the preferredembodiments are made by way of example rather than to limit the scope ofthe invention, and it is intended to cover within the spirit and scopeof the invention all such changes and modifications.

1. A method of performing image mark recognition, comprising: accessinga scanned image of a document containing a plurality of image marks;performing reference image mark recognition on the scanned image;performing coordinate mapping on the scanned image to determinecoordinates for a plurality of cells within the scanned image, whereineach cell comprises a plurality of pixels; analyzing one or more pixelsin each cell; and determining a cell color value for each cell based onvalues assigned to the one or more pixels.
 2. The method of claim 1wherein performing reference image mark recognition comprisesdetermining a location for each of one or more alignment marks.
 3. Themethod of claim 2, further comprising verifying image mark alignment andspacing based on a resolution of the scanned image and the locations ofthe one or more alignment marks.
 4. The method of claim 2 whereindetermining the location of one or more alignment marks comprisesexamining each corner of the scanned image.
 5. The method of claim 2wherein determining the location of one or more alignment markscomprises searching for trigger rows on at least one margin of thescanned image. 6-11. (canceled)
 12. The method of claim 1 whereinanalyzing one or more pixels comprises incrementing a total color valuefor the cell by a color value for each pixel.
 13. The method of claim 12wherein determining a cell color value comprises setting the cell colorvalue to the ratio of the total color value to a maximum color value.14. A system for performing image mark recognition, comprising: aprocessor; and one or more computer readable mediums operatively coupledto the processor, wherein at least one of the one or more computerreadable mediums contains a scanned image of a document, wherein atleast one of the one or more computer readable mediums contains computerprogram instructions for performing a method of performing image markrecognition, the method comprising: accessing a scanned image of adocument containing a plurality of image marks, performing referenceimage mark recognition on the scanned image, performing coordinatemapping on the scanned image to determine coordinates for a plurality ofcells within the scanned image, wherein each cell comprises a pluralityof pixels analyzing one or more pixels in each cell, and determining acell color value for each cell based on values assigned to the one ormore pixels.
 15. The system of claim 14 wherein the computer programinstructions for the step of performing reference image mark recognitioncomprise determining a location for each of one or more alignment marks.16. The system of claim 15 wherein the computer program instructions forthe step of performing reference image mark recognition further compriseverifying image mark alignment and spacing based on a resolution of thescanned image and the locations of the one or more alignment marks. 17.The system of claim 15 wherein the computer program instructions for thestep of determining the location of one or more alignment marks compriseexamining each corner of the scanned image.
 18. The system of claim 15wherein the computer program instructions for the step of determiningthe location of one or more alignment marks comprise searching fortrigger rows on at least one margin of the scanned image. 19-25.(canceled)
 26. The system of claim 14 wherein the computer programinstructions for the step of analyzing one or more pixels compriseincrementing a total color value for the cell by a color value for eachpixel.
 27. The system of claim 26 wherein the computer programinstructions for the step of determining a cell color value comprisesetting the cell color value to the ratio of the total color value to amaximum color value.